Maximum Entropy and Bayesian Methods in Applied Statistics

Klappentext This collection of papers contains contributions showing the use of the maximum entropy method in many of the fields in which it finds application. Zusammenfassung This collection of papers by leading researchers in their respective fields contains contributions showing the use of the maximum entropy method in many of the fields in which it finds application. In the physical! mathematical and biological sciences it is often necessary to make inferences based on insufficient data. Inhaltsverzeichnis 1. Bayesian Methods: General Background E. T Jaynes; 2. Monkeys, Kangaroos, and N E. T Jaynes; 3. The Theory and Practice of the Maximum Entropy Formalism R. D. Levine; 4. Bayesian Non-Parametric Statistics Stephen F. Gull and John Fielden; 5. Generalized Entropies and the Maximum Entropy Principle J. Aczel and B. Forte; 6. The Probability of a Probability John F. Cyranski; 7. Prior Probabilities Revisited N. C Dalkey; 8. Band Extensions, Maximum Entropy and the Permanence Principle Robert L. Ellis, Israel Gohberg and David Lay; 9. Theory of Maximum Entropy Image Reconstruction John Skilling; 10. The Cambridge Maximum Entropy Algorithm John Skilling; 11. Maximum Entropy and the Moments Problem: Spectroscopic Applications C. G. Gray; 12. Maximum-Entropy Spectrum from a Non-Extendable Autocorrelation Function Paul F. Fougere; 13. Multichannel Maximum Entropy Spectral Analysis Using Least Squares Modelling P. A. Tyraskis; 14. Multichannel Relative-Entropy Spectrum Analysis Bruce R. Musicus and Rodney W. Johnson; 15. Maximum Entropy and the Earth's Density E. Rietsch; 16. Entropy and Some Inverse Problems in Exploration Seismology James H. Justice; 17. Principle of Maximum Entropy and Inverse Scattering Problems Ramarao Inguva and James Baker-Jarvis.

Résumé
This collection of papers by leading researchers in their respective fields contains contributions showing the use of the maximum entropy method in many of the fields in which it finds application. In the physical, mathematical and biological sciences it is often necessary to make inferences based on insufficient data.

Contenu

1. Bayesian Methods: General Background E. T Jaynes; 2. Monkeys, Kangaroos, and N E. T Jaynes; 3. The Theory and Practice of the Maximum Entropy Formalism R. D. Levine; 4. Bayesian Non-Parametric Statistics Stephen F. Gull and John Fielden; 5. Generalized Entropies and the Maximum Entropy Principle J. Aczel and B. Forte; 6. The Probability of a Probability John F. Cyranski; 7. Prior Probabilities Revisited N. C Dalkey; 8. Band Extensions, Maximum Entropy and the Permanence Principle Robert L. Ellis, Israel Gohberg and David Lay; 9. Theory of Maximum Entropy Image Reconstruction John Skilling; 10. The Cambridge Maximum Entropy Algorithm John Skilling; 11. Maximum Entropy and the Moments Problem: Spectroscopic Applications C. G. Gray; 12. Maximum-Entropy Spectrum from a Non-Extendable Autocorrelation Function Paul F. Fougere; 13. Multichannel Maximum Entropy Spectral Analysis Using Least Squares Modelling P. A. Tyraskis; 14. Multichannel Relative-Entropy Spectrum Analysis Bruce R. Musicus and Rodney W. Johnson; 15. Maximum Entropy and the Earth's Density E. Rietsch; 16. Entropy and Some Inverse Problems in Exploration Seismology James H. Justice; 17. Principle of Maximum Entropy and Inverse Scattering Problems Ramarao Inguva and James Baker-Jarvis.